US7492485B2ExpiredUtilityPatentIndex 84
Image-based compensation and control of photoreceptor ghosting defect
Est. expiryOct 20, 2025(expired)· nominal 20-yr term from priority
G03G 15/5062G03G 2215/00042
84
PatentIndex Score
11
Cited by
4
References
19
Claims
Abstract
A system and method for correcting a defect in an image, such as a ghost defect or a reload defect, by compensating for the defect. A defect model is created with a source target function that represents a source level with respect to a target level. A test output image is created on which the test data is measured. State data representing a state of the imaging device, previously printed images or the current image are inputted to a controller. An image correction factor is outputted from the controller based on the test image measurement data, the state data, the previously printed images, and the current image to the image path actuator. A corrected image is created based on the image correction factor.
Claims
exact text as granted — not AI-modified1. A method for correcting a defect in an image by compensating for the defect, the method comprising:
inputting a test image to an image path actuator;
inputting an output of the image path actuator to a marking engine;
creating a test output image;
measuring test data on the test output image;
inputting the test measurement data obtained from the test output image to a controller;
storing previously printed images in an image buffer;
inputting the previously printed images from the image buffer to the controller;
inputting the current image to the controller;
outputting an image correction factor from the controller based on the test measurement data, the previously printed images, and the current image to the image path actuator; and
creating a corrected image based on the image correction factor output from the controller to the image path actuator,
wherein the step of outputting an image correction factor includes implementing the formula
Δ
t
in
=
-
g
(
t
in
,
s
in
)
∂
ERC
∂
t
in
+
∂
g
∂
t
in
,
wherein Δt in is the correction factor, t in is an input gray level, s in is a ghost source input gray level, ERC is an engine response curve, and g is the magnitude of the ghost defect.
2. The method of claim 1 , wherein the image defect is a ghost defect.
3. The method according to claim 1 , wherein the image defect is a reload defect.
4. The method according to claim 1 , further comprising the steps of inputting state data representing a state of the imaging device to the controller, and modifying the correction factor based on the state data.
5. The method according to claim 1 , further comprising creating a defect model, and outputting the correction factor based on the defect model.
6. The method according to claim 5 , wherein creating a defect model further includes creating a source target function that represents an entire range of a source level with respect to an entire range of a target level.
7. The method according to claim 1 , wherein each step of the method is performed individually for every pixel of an image.
8. The method according to claim 1 wherein the image correction is performed at a spatial distance equal to one revolution of a photoreceptor or some multiple of revolutions of the photoreceptor from an original image.
9. The method according to claim 1 , wherein the steps of the method are repeated iteratively.
10. An image defect correction system, comprising:
an image path actuator receiving a test input image from an imaging device;
a marking engine receiving information from the image path actuator and creating a test output image;
a measuring device obtaining data from the test output image;
an image buffer containing previously printed images;
a controller receiving the test measurement data from the measuring device, the image buffer, and a current image, determining a correction factor, and supplying the correction factor to the image path actuator,
wherein the image path actuator receives a correction factor from the controller and the current image from the imaging device, and supplies a corrected image to the marking engine, and
the correction factor is based on the formula
Δ
t
in
=
-
g
(
t
in
,
s
in
)
∂
ERC
∂
t
in
+
∂
g
∂
t
in
,
where Δt in is the correction factor, t in is an input gray level, s in is a ghost source input gray level, ERC is an engine response curve, and g is the magnitude of the ghost.
11. The image defect corrections system according to claim 10 , wherein the defect is a ghost defect.
12. The image defect correction system according to claim 10 , wherein the defect is a reload defect.
13. The image defect correction system according to claim 10 , wherein the controller also receives data regarding a state of the imaging device and considers the data regarding the state of the imaging device in creating the correction factor.
14. The image defect correction system according to claim 10 , wherein the controller creates a defect model that is used in obtaining the correction factor.
15. The image defect correction system according to claim 14 , wherein the defect model includes a source target function that represents an entire range of a source level with respect to an entire range of a target level.
16. The image defect correction system according to claim 10 , wherein the controller obtains the correction factor individually for every pixel of the image.
17. The image defect correction system according to claim 10 , wherein a correction is implemented at a spatial distance equal to an integer multiple of one revolution of a photoreceptor.
18. The image defect correction system according to claim 10 , wherein the controller performs an iterative correction to obtain the correction factor.
19. The image defect correction system according to claim 10 , wherein the buffer contains previously printed data for at least one complete revolution of a photoreceptor.Cited by (0)
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